A Study to Evaluate Safety and Immunogenicity of the ExPEC4V Clinical Trial Material After a Single Intramuscular Dose and a Second Dose 6 Months Later in Healthy Participants Aged 18 Years and Older: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study to Evaluate Safety and Immunogenicity of the ExPEC4V Clinical Trial Material After a Single Intramuscular Dose and a Second Dose 6 Months Later in Healthy Participants Aged 18 Years and Older (NCT03500679), a randomized phase 2 study. The primary outcome is Percentage of Participants With Solicited Local Adverse Events (AEs) After First Vaccination.

2. Clinical Question

The central statistical comparison concerns the frequency of these specifically solicited local events after the first vaccination. The registry reports event percentages for ExPEC4V and placebo, each with a 95% confidence interval, along with a risk-difference estimate and an unadjusted p-value. These summaries describe the observed groups and the uncertainty around the comparison; they do not establish that an event was caused by the vaccine. The adverse-event definition explicitly includes occurrences whether or not they are considered related to a study product.

3. Trial Design

This was a Phase 2, randomized, double-blind, placebo-controlled, parallel-group study. The registry lists an enrollment of 100 healthy participants aged 18 years and older. The study status is completed. The registry gives a start date of 2018-05-09 and a primary completion date of 2018-11-05.

Participants were assigned to ExPEC4V or matching placebo. The ExPEC4V group received intramuscular injections into the deltoid muscle on Days 1 and 181. The placebo group received matching intramuscular injections on the same days. The primary endpoint concerns the first vaccination, with solicited local adverse events assessed during the interval from Day 1 to Day 15. The registry also describes immunogenicity measurements, including an ELISA assessment on Day 15 in the study purpose and additional antibody outcomes in the listed secondary outcomes.

The primary endpoint analysis population was the full analysis set. It included randomized participants with at least one study-vaccine administration documented, even when protocol deviations occurred. The registry record does not report the original sample-size justification, the method used to generate the randomization sequence, allocation concealment procedures, or operational details of blinding. It also does not report a statistical analysis plan or any interim analyses. Those features should not be inferred from the randomized and double-blind design labels.

The primary endpoint is one among a larger set of planned outcome measures. The record lists 21 outcome measures and 13 posted secondary outcomes, while no analysis count is posted in the analysis field. These registry entries describe the scope of the study, but do not by themselves establish which analyses were prespecified, how multiplicity was addressed, or whether all planned outcomes were reported.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The full analysis set (FAS) included all randomized participants with at least one study vaccine administration documented regardless of the occurrence of protocol deviations.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants With Solicited Local Adverse Events (AEs) After First Vaccination, measured over 14 days after first vaccination (Day 1 to Day 15).

The primary endpoint is the percentage of participants with solicited local adverse events during the 14 days after the first vaccination, from Day 1 to Day 15. Solicited events are defined local reactions about which participants were specifically asked and which they recorded in a diary. The listed reactions are injection-site pain or tenderness, injection-site erythema, and injection-site swelling or induration.

A percentage is a direct way to describe how common a specified event was among the participants in an analysis group. It is especially interpretable for an endpoint recorded as present or absent over a stated observation period. The registry defines an adverse event broadly as an untoward medical occurrence after administration of a medicinal product; an event need not be judged causally related to that product. Thus, the endpoint describes reported events after vaccination, not a determination that the vaccination caused them.

Soliciting specific reactions and collecting them in a diary can make reporting more systematic than relying only on spontaneous reports. That approach also means the endpoint is limited to the local reactions and assessment period specified in the record. It does not represent every possible adverse event or the overall safety profile. The endpoint is reported as a percentage with a 95% confidence interval, which helps show both the observed frequency and the uncertainty associated with the estimate.

7. Results Posted in the Registry

• ExPEC4V: 38.7% (29/75) versus 20.0% (5/25) on control; risk difference 18.7 percentage points (95% CI -0.5 to 37.8), risk ratio 1.93 (0.84–4.45); unadjusted two-proportion z-test p = 0.088.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level for the specified follow-up period: a participant either had at least one solicited local adverse event as defined for the endpoint or did not. The registry expresses the group results as percentages of participants. This type of summary is useful because it states the observed frequency directly rather than describing a continuous measurement such as a laboratory concentration.

What does a confidence interval describe?

A confidence interval is a statistical range that conveys uncertainty around an estimate. In repeated use of the same method under its assumptions, intervals constructed in this way would cover the underlying parameter at the stated confidence level at the stated long-run rate. It is not a range containing a specified proportion of individual participants, and it does not give the probability that the true value lies in this particular calculated interval.

The registry reports 95% confidence intervals for both group percentages and for the risk difference. The intervals for the group percentages express uncertainty in each group’s event frequency. The risk-difference interval expresses uncertainty in the contrast between groups. Considering the direct contrast is important: separate group estimates alone do not quantify the uncertainty in their difference.

How should the risk difference be read?

The risk difference is a subtraction-based contrast between the two event proportions, expressed in the posted results as 0.187. Its confidence interval runs from -0.005 to 0.378. Zero represents no difference in the two proportions on this scale. Because the interval includes zero, the data are compatible with no difference as well as with a range of positive differences; the interval also allows a small negative difference. The point estimate alone should not be treated as the exact underlying contrast.

The record also includes a risk ratio and an odds ratio with confidence intervals. These are alternative ways of expressing a binary-outcome comparison. A ratio of risks compares the event frequencies proportionally, whereas an odds ratio compares odds, which are not the same quantity as probabilities. Such measures can give useful complementary descriptions, but their interpretations depend on the scale. The primary explanation emphasizes the risk difference because it directly expresses the absolute contrast in event proportions.

What does the p-value contribute?

The posted unadjusted p-value is 0.088. In general, a p-value describes how unusual data at least as inconsistent with a specified null hypothesis would be if that null hypothesis and the test assumptions were true. It is not the probability that the null hypothesis is true, nor does it measure the clinical importance of the observed difference. Since the record labels this value unadjusted, it should not be assumed to account for testing across multiple outcomes or comparisons.

Interpretation of a p-value also depends on the analysis plan, which is not reported in the registry record. The record does not identify the test used for this comparison or document an adjustment for multiplicity. The p-value should therefore be read as the posted unadjusted result, alongside the effect estimate and interval, rather than as a complete account of the study’s inferential framework.

Why do event counts and group sizes matter?

Percentages are based on a numerator and a denominator. Their precision depends in part on how many participants are observed and how frequently the event occurs. A smaller group generally provides less information about its event proportion, all else equal. The placebo group contains fewer participants than the ExPEC4V group, and its confidence interval is correspondingly broad. The interval is the more informative summary of precision than the percentage alone.

The analysis population definition matters as well. The full analysis set includes randomized participants who had at least one documented study-vaccine administration, regardless of protocol deviations. The registry record does not report how many randomized participants, if any, were excluded from this endpoint’s analysis or how missing diary information was handled. It is therefore not possible from the record to assess the effect of missing outcome data or to reconstruct the denominator rules in greater detail.

What does over-dispersion mean in general?

Over-dispersion is a general concern when data vary more than a statistical model assumes. In binary participant-level data, a simple proportion-based analysis does not automatically involve the same over-dispersion issue that can arise in count models, but clustering or repeated observations could require additional modeling. The record does not describe a model for the primary endpoint, a clustering adjustment, or repeated-measures treatment. It would be inappropriate to assert that any such issue arose or was addressed in this study.

Overall, the available summaries permit an interpretation of the observed percentages and their reported uncertainty. They do not reveal every analytical choice, including the test procedure, assumptions checked, missing-data strategy, or handling of multiple outcomes. Those elements are not reported in the registry record.

10. Confidence Intervals and Precision

The ExPEC4V event percentage is 38.7%, with a 95% confidence interval from 27.64% to 50.62%. The placebo percentage is 20.0%, with a 95% confidence interval from 6.83% to 40.7%. These intervals show that the point estimates should not be read as exact values for the underlying event frequencies. Both intervals cover a substantial range of plausible values under the interval method.

The placebo interval is especially broad, and the placebo group has a reported size of 25.0 compared with 75.0 in the ExPEC4V group. With fewer participants, the event percentage is estimated less precisely. The ExPEC4V interval is also wide enough that the observed percentage should not be treated as a highly precise estimate.

For the comparison, the risk difference is 0.187 and its 95% confidence interval extends from -0.005 to 0.378. Because this interval includes zero and ranges over both negative and positive values, the comparison does not precisely determine the direction and magnitude of the underlying difference. Its upper end also permits a substantially larger positive difference than the point estimate. Precision is therefore limited even though the point estimate favors a higher observed percentage in the ExPEC4V group.

Confidence intervals are not guarantees that the true value lies inside a particular interval, and their width does not describe variation among individual participants. They characterize uncertainty in estimated group-level quantities under the method’s assumptions. The registry record does not identify the interval-construction method, so additional method-specific assumptions cannot be evaluated.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The sample-size planning illustration translates the observed risk difference into hypothetical planning targets. For a binary endpoint such as this one, the entries are participants per arm, not total events. The displayed scenarios plan for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. The corresponding estimates are 93, 157, and 334 participants per arm for 80% power, and 123, 210, and 447 participants per arm for 90% power.

The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. The registry’s original design assumptions and sample-size justification are not reported in the registry record; these figures are an illustration computed from the observed effect, not the documented design basis for the trial.

In plain language, the 80% power column gives the estimated number of participants per arm for a hypothetical study to have an 80% chance of detecting the specified effect under the planning assumptions. The 90% column gives the corresponding estimate for a 90% chance. These are planning probabilities conditional on the assumed effect and statistical model, not guarantees about a future study. Smaller target effects require more participants, which is why the estimates rise when planning for a smaller fraction of the observed effect.

These calculations are not observed power. They are forward-looking planning illustrations based on the observed estimate and should not be read as a measure of how well powered the completed trial was.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.200; treatment proportion p₁ = 0.387; average p̄ = 0.293.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6439 = 1.2620.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6302 = 0.5304.
4. n = (1.2620 + 0.5304)² / (0.1867)² = 92.2, rounded up to 93 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.2                          # control proportion
p1 <- 0.386666666666667                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(3500679)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 93 (80% power), 123 (90% power)
 75% of observed effect: n per arm = 157 (80% power), 210 (90% power)
 50% of observed effect: n per arm = 334 (80% power), 447 (90% power)
power.prop.test: 92.2 
Simulated power at n = 93 per arm: 0.807 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Multiplicity, Missing Data and Analysis Populations

The study covers more outcomes than the primary local adverse-event endpoint. The registry lists 21 outcome measures and 13 posted secondary outcomes, including adverse events after the second vaccination and immunogenicity outcomes assessed using OPKA and ELISA. With multiple outcomes or comparisons, the chance of obtaining at least one apparently unusual result can increase if each is tested without adjustment. This is the general reason multiplicity matters when interpreting collections of statistical tests.

The registry record does not report a multiplicity strategy for the primary and secondary outcomes. It does not state whether outcomes were tested in a hierarchy, whether any adjustment was planned, or whether the posted p-value is part of a broader confirmatory testing procedure. The primary comparison’s p-value is identified as unadjusted, so it should not be assumed to account for the other outcomes. The record also does not report an analysis plan that would clarify how the endpoint family was defined.

Missing-data handling is also not reported in the registry record. The full analysis set includes randomized participants with at least one documented study-vaccine administration, regardless of protocol deviations. However, the record does not state whether all such participants had evaluable diary data for the primary endpoint, how incomplete diaries were treated, or whether any observations were imputed or excluded. Consequently, the displayed percentages and intervals cannot be used to determine the impact of missing endpoint data.

The endpoint population definition and the analysis population for every secondary outcome may differ; the registry record does not provide enough detail to establish those rules across outcomes. It also does not report sensitivity analyses for alternative missing-data assumptions. These gaps do not invalidate the posted summaries, but they limit how fully the analysis can be independently assessed and how confidently one can generalize beyond the participants with recorded endpoint information.

14. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 3% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: osteoarthritis (4.0%), breast cancer (1.3%), deep vein thrombosis (1.3%).

The registry lists serious adverse events in 2 participants in the ExPEC4V group and 1 participant in the placebo group. The corresponding groups at risk are 75 and 25 participants, respectively. Deaths are listed as 0 in each group. These are counts, not estimates of a causal effect, and should be read alongside the group sizes and the study’s limited enrollment.

The posted serious-event terms include Osteoarthritis at 4.0%, Breast Cancer at 1.3%, and Deep Vein Thrombosis at 1.3%. The record does not give enough detail in these summaries to assign each term to a study group, establish whether events were considered related to study product, or interpret the clinical course. An adverse event may occur after treatment without being caused by it.

Rare serious events are difficult to characterize precisely in a study of this size. The counts cannot establish comparative safety for uncommon outcomes, and zero reported deaths does not establish that a risk is absent. The registry’s serious-event totals should be interpreted as descriptive safety reporting over the study, not as proof for or against a causal association.

15. What the Result Does, and Does Not, Mean

The posted primary endpoint shows that solicited local adverse events were recorded in 38.7% of the ExPEC4V group and 20.0% of the placebo group during the specified period after the first vaccination. The estimated risk difference is 0.187, with a 95% confidence interval from -0.005 to 0.378, and the unadjusted p-value is 0.088. Together, these figures describe the observed group results and considerable uncertainty about the comparison.

The results do not establish that ExPEC4V caused the reported local events. The registry’s adverse-event definition does not require a causal relationship, and the event endpoint records occurrence rather than attribution. Nor do the results describe severity, duration, or every possible safety outcome. The primary endpoint is confined to solicited local reactions during the 14 days after the first vaccination; it should not be substituted for findings after the second vaccination or for the study’s immunogenicity outcomes.

The point estimate is higher in the ExPEC4V group, but its confidence interval includes zero and allows a range of possible differences. The unadjusted p-value should not be interpreted as the probability that the observed pattern is due to chance or as a measure of clinical importance. The posted data do not support a precise conclusion about the magnitude of the underlying difference.

These findings are from a Phase 2 study with 100 participants enrolled and unequal group sizes. They do not establish how findings would generalize to populations beyond the healthy participants aged 18 years and older described in the registry. The record does not report the original sample-size rationale, multiplicity plan, or missing-data procedures, so those aspects cannot be incorporated into a fuller assessment of the evidence.

16. Why This Trial Matters Statistically

This trial illustrates why a group percentage should be read together with its denominator and confidence interval. The ExPEC4V estimate is 38.7% and the placebo estimate is 20.0%, but the groups differ in size and the intervals are wide, particularly for placebo. The risk-difference interval adds a direct uncertainty statement about the comparison and crosses zero. Looking only at the point estimates would give an incomplete account of what the data can establish.

It also demonstrates the distinction between an event recorded after vaccination and an event caused by vaccination. Solicited diary-based events provide a defined, systematic endpoint, but the registry’s definition does not require a causal relationship. Separating occurrence, attribution, and severity helps prevent an endpoint percentage from being interpreted more broadly than its definition allows.

The study also has a broad outcome scope: the record lists immunogenicity outcomes and adverse-event outcomes in addition to the primary endpoint. That scope makes multiplicity and transparent analysis plans relevant statistical considerations. The registry does not report how multiplicity or missing observations were handled, so the posted primary comparison cannot be assumed to represent an isolated or fully documented testing strategy.

Finally, the planning illustrations show how sample-size requirements depend on the effect a future study aims to detect. They are distinct from the completed study’s enrollment and do not reveal the original design rationale. Keeping observed estimates, uncertainty, and hypothetical planning calculations separate is essential to a sound statistical reading.

17. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The registry record leaves several trial-specific questions unresolved. Although it identifies the study as randomized and double-blind, it does not describe sequence generation, allocation concealment, or how masking was maintained. It also does not report the original sample-size justification, so the intended precision or power for the primary endpoint cannot be assessed from the record.

The primary endpoint is based on solicited local events collected in participant diaries. The record specifies the reactions and assessment period, but does not report the criteria for event grading, completeness of diary return, handling of missing diary entries, or how the reported percentages were derived when data were incomplete. It also does not report the method used to construct the confidence intervals or the test underlying the unadjusted p-value.

There were 75.0 participants in the ExPEC4V group and 25.0 in the placebo group for the reported primary analysis. The unequal group sizes and limited enrollment constrain precision, particularly for the smaller comparator group and for uncommon events. Serious adverse-event counts are descriptive and do not resolve risks for rare outcomes.

The record lists multiple outcome measures but does not report a multiplicity plan, a complete statistical analysis plan, or interim-analysis details. The number of secondary outcomes posted is 13, while the record lists 21 outcome measures; the registry entries do not explain the reporting status of every measure. These limitations affect assessment of the analysis and completeness of outcome reporting, without changing the values of the posted summaries.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: A Study to Evaluate Safety and Immunogenicity of the ExPEC4V Clinical Trial Material After a Single Intramuscular Dose and a Second Dose 6 Months Later in Healthy Participants Aged 18 Years and Older — NCT03500679.
• Registry record last updated 2019-11-26; status last verified 2019-11.
• Results first posted 2019-11-26.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

NCT03500679 is a completed Phase 2 randomized, double-blind, placebo-controlled, parallel-group study of ExPEC4V in healthy participants aged 18 years and older. The registry lists enrollment of 100 participants and intramuscular ExPEC4V or matching placebo injections on Days 1 and 181.

The primary endpoint was the percentage of participants with solicited local adverse events from Day 1 to Day 15. The reported percentages were 38.7% for ExPEC4V and 20.0% for placebo. The risk difference was 0.187, with a 95% confidence interval from -0.005 to 0.378, and the unadjusted p-value was 0.088. The interval indicates substantial uncertainty around the comparison.

The registry also lists safety and immunogenicity outcomes. Details about the original sample-size rationale, multiplicity strategy, and missing-data handling are not reported in the registry record.